Literature DB >> 17958182

Physical activity and sedentary lifestyle in children as time-limited functions: usefulness of the principal component analysis method.

Comlavi B Guinhouya1, Stephane Soubrier, Christian Vilhelm, Pierre Ravaux, Mohamed Lemdani, Alain Durocher, Hervé Hubert.   

Abstract

This study was designed to examine the hourly variation in and the interplay between physical activity and sedentary behavior (SB) in order to highlight key time periods for physical activity interventions for children. Data for physical activity and SB obtained with ActiGraph in 56 boys and 47 girls aged from 8 to 11 years. These data were divided into sixty minute-time samples for moderate-to-vigorous physical activity (MVPA) and SB, and analyzed using a principal component analysis (PCA) and correlation statistics. The PCA provides 10 factors which account for 80.4% of the inertia. Only two of these factors did not display competition between MVPA and SB. Contrary to some reports, a coefficient of correlation of -.68 (p < 10(-4)) was found between daily time spent at MVPA and SB. Some salient traits of children's behaviors were shown through PCA. The results suggested that efficacy of interventions targeting the morning hours (07:00 AM-11:59 AM) and the afternoon period (02:00 PM-05:59 PM) warrants attention.

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Year:  2007        PMID: 17958182     DOI: 10.3758/bf03193040

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  1 in total

1.  Segmenting accelerometer data from daily life with unsupervised machine learning.

Authors:  Dafne van Kuppevelt; Joe Heywood; Mark Hamer; Séverine Sabia; Emla Fitzsimons; Vincent van Hees
Journal:  PLoS One       Date:  2019-01-09       Impact factor: 3.240

  1 in total

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